Independent parameters of the rotation tensor ##R_{ij}##

In summary, the conversation revolves around a problem involving a rotation matrix and its parameters. The individual attempted to solve the problem by writing the matrix in the form of a square matrix with elements and using the matrix form of the orthogonality relation. However, they encountered some difficulties and requested help. The other person provided a hint and the individual was able to solve the problem by realizing that the number of independent variables involved is reduced by the number of independent constraint equations. In this case, there were six such equations, resulting in a reduction of three independent parameters for the rotation matrix.
  • #1
brotherbobby
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Homework Statement
Show how the ##\text{orthogonality condition}## of the rotation matrix ##R_{ij} R_{ik} = \delta _{jk}## diminishes up to ##\mathbf{three}## the number of independent parameters of the matrix.
Relevant Equations
An arbitrary vector ##\vec x## upon rotated by the matrix ##\mathbb R## results in a new vector ##\vec x'## given by ##\vec x' = \mathbb{R} \vec x##, or in component notation : ##x'_i = \rm R_{ij} x_j##, where ##\rm R_{ij}## are the components of the rotation matrix.

Due to orthogonality, these components satisfy the requirement : ##R_{ij} R_{ik} = \delta _{jk}##.
I am afraid I had no credible attempt at solving the problem.

My poor attempt was writing the matrix ##\mathbb R## as a ##3 \times 3## square matrix with elements ##a_{ij}## and use the matrix form of the orthogonality relation ##\mathbb R^T \mathbb R = \mathbb I##, where ##\mathbb I## is the identity matrix with diagonal elements 1 and off diagonal elements 0. Those a's are the parameters of the rotation matrix. I obtained 9 equations for the a's, some identical, but found that almost all the a's would cancel to leave only 1 independent component!

Any help would be welcome.
 
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  • #2
This type of problem can be solved simply by counting the number of independent parameters that you start with (which I hope you've already realized is ##3\times 3 = 9##), and subtracting the number of independent constraint equations, which in this case is ... ?

Hint: is ##\delta_{jk}## symmetric, anti-symmetric, or neither?
 
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  • #3
Very sorry for the late reply. Thank you for the hint above, which really leads easily to the solution.

We know that the set of relations (constraints) that variables have, lead to a decline in how many of them are independent. The more such relations (expressed as equations), the lower the number of independent variables involved.

In our problem above, these variables are the components of the rotation tensor ##R_{ij}##. But they satisfy some relations, compactly written as ##R_{ij} R_{ik} = \delta_{jk}##. How many relations are these? Nine, on first glance, but they are not all independent. The kronecker tensor being symmetric, we have the number of independent equations as its number of independent components : ##N = \tfrac{3(3+1)}{4} = 6##.

These six relations serve to reduce the number of independent parameters of the rotation matrix by ##9 - 6 = \boxed{3}##.
 
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What is the rotation tensor?

The rotation tensor is a mathematical object used to describe the rotation of a three-dimensional object. It is a 3x3 matrix that represents the transformation of coordinates from one frame of reference to another due to rotation.

What are the independent parameters of the rotation tensor?

The independent parameters of the rotation tensor are the three angles of rotation around the x, y, and z axes. These angles are typically denoted as α, β, and γ, respectively.

How are the independent parameters related to the rotation tensor?

The independent parameters are used to construct the rotation tensor using a specific mathematical formula. Each angle corresponds to a specific element in the rotation tensor, and together they determine the orientation of the rotated object.

Can the rotation tensor be used to rotate any object?

Yes, the rotation tensor can be used to rotate any three-dimensional object. It is a fundamental concept in linear algebra and is used in various fields such as physics, engineering, and computer graphics.

What are some applications of the rotation tensor?

The rotation tensor has many applications, including describing the orientation of rigid bodies in physics, modeling the motion of objects in computer graphics, and calculating the transformation of coordinates in robotics and navigation systems.

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